Cry Patterns Research Articles

Use of psychoacoustic spectrum warping, decision template fusion, and neighborhood component analysis in newborn cry diagnostic systems.

Dealing with newborns' health is a delicate matter since they cannot express needs, and crying does not reflect their condition. Although newborn cries have been studied for various purposes, there is no prior research on distinguishing a certain pathology from other pathologies so far. Here, an unsophisticated framework is proposed for the study of septic newborns amid a collective of other pathologies. The cry was analyzed with music inspired and speech processing inspired features. Furthermore, neighborhood component analysis (NCA) feature selection was employed with two goals: (i) Exploring how the elements of each feature set contributed to classification outcome; (ii) investigating to what extent the feature space could be compacted. The attained results showed success of both experiments introduced in this study, with 88.66% for the decision template fusion (DTF) technique and a consistent enhancement in comparison to all feature sets in terms of accuracy and 86.22% for the NCA feature selection method by drastically downsizing the feature space from 86 elements to only 6 elements. The achieved results showed great potential for identifying a certain pathology from other pathologies that may have similar effects on the cry patterns as well as proving the success of the proposed framework.

IoT Baby Monitoring System Using Node MCU

This paper presents an idea to design a Smart Cradle System using IOT which will help the parents to monitor their child even if they are away from home & detect every activity of the Baby from any distant corner of the world. It is an innovative, smart & protective Cradle System to nurture an infant in an efficient way. This system considers all the minute details required for the care & protection of the Baby in the cradle. The design of smartness & innovation comes with the use of technologies/methodologies which include the Internet of Things (IoT) (Modules like Arduino UNO, Humidity & Temperature sensing, etc..,), Cry Detecting Mechanism, Live Video Surveillance, Cloud Computing (Data Storage) & User Friendly Web application (for User Controls). In order to detect each & every activity of the Baby, different Sensors/Modules are attached to the Cradle: Humidity & Temperature Sensing Module for detection of Wetness of the bed, A Camera on top of the Cradle for live video footage & Cry Detection Circuit to analyze Cry Patterns. All the data which has been taken from the sensors/modules will be stored in Cloud? & analyzed at regular intervals.

A Scientometric Review of Infant Cry and Caregiver Responsiveness: Literature Trends and Research Gaps over 60 Years of Developmental Study.

Infant cry is an adaptive signal of distress that elicits timely and mostly appropriate caring behaviors. Caregivers are typically able to decode the meaning of the cry and respond appropriately, but maladaptive caregiver responses are common and, in the worst cases, can lead to harmful events. To tackle the importance of studying cry patterns and caregivers' responses, this review aims to identify key documents and thematic trends in the literature as well as existing research gaps. To do so, we conducted a scientometric review of 723 documents downloaded from Scopus and performed a document co-citation analysis. The most impactful publication was authored by Barr in 1990, which describes typical developmental patterns of infant cry. Six major research thematic clusters emerged from the analysis of the literature. Clusters were renamed "Neonatal Pain Analyzer" (average year of publication = 2002), "Abusive Head Trauma" (average year of publication = 2007), "Oxytocin" (average year of publication = 2009), "Antecedents of Maternal Sensitivity" (average year of publication = 2010), "Neurobiology of Parental Responses" (average year of publication = 2011), and "Hormonal Changes & Cry Responsiveness" (average year of publication = 2016). Research clusters are discussed on the basis of a qualitative inspection of the manuscripts. Current trends in research focus on the neurobiology of caregiver responses and the identification of factors promoting maternal sensitivity. Recent studies have also developed evidence-based strategies for calming crying babies and preventing caregivers' maladaptive responses. From the clusters, two topics conspicuously call for future research: fathers' responsiveness to infant cry and the impact of caregiver relationship quality on cry responsiveness.

Smart Infant Cradle in Clinical Perspective using H-IoT with Android Application

In scheduled time monitoring the infants in a hospital or at home where the monitoring with human resources, especially nurses is exceptionally difficult. So, these infants can be monitored 24*7 using a device. Infant health monitoring became a fast-growing technology in the medical field. Hence, we are implementing an H-IoT where health monitoring sensors are used. A smart cradle, put into practice which utilizes the basic data from the infant-like heartbeat pulses, temperature, bed wetness, cry pattern, and movement. These parameters-related sensors are associated with the Arduino UNO to keep track of these, the various parameters are displayed in the dashboard. If the system notifies any unforeseen changes in the infant, then it will spontaneously caution the infant status in call notification using the Global System of Mobile Communication module. In this manner, IoT health monitoring is fetched for the monitoring of infants in a real-time environment.

Microencapsulated Tuna Oil Results in Higher Absorption of DHA in Toddlers.

Docosahexaenoic acid (DHA) is an essential component for brain and visual acuity development during foetal and early postnatal life. A newly released directive under the European Commission stipulates DHA as a mandatory ingredient in infant formula. This poses challenges to manufacturers in preserving the stability and bioavailability of DHA at levels akin to human breast milk. The aims of this study were (a) to investigate the bioavailability of microencapsulated omega-3 DHA formulations in healthy toddlers compared with high DHA fish oil for a one-month period and (b) to assess the effect of DHA supplementation on children’s sleep and cry patterns. Sixty toddlers were randomly allocated to four groups: 1. unfortified formula, 2. unfortified formula plus high DHA tuna oil, 3. fortified formula with dairy-based microencapsulated high DHA tuna oil powder, and 4. fortified formula with allergenic-free microencapsulated high DHA tuna oil powder. Bioavailability was assessed from both blood and faecal fatty acid levels. The results showed an enhanced bioavailability with significantly greater concentrations of blood DHA levels in formulas with microencapsulated powders. There were no significant effects of treatment on sleep and cry patterns. Application and delivery of microencapsulated DHA tuna oil powder in toddlers’ formula provided better bioavailability of the active DHA.

The Effect of Injectable Medication Procedure on the Level of Pain among Early Childhood patients

Abstract Children are often exposed to painful procedures during hospitalization. Validated age appropriate scales are available to assess pain among pediatric patients. The aim of this study is to find out the effect of injectable medication procedure on the level of pain among early childhood patients. This descriptive cross -sectional study was designed to assess the physiological and behavioral characteristic of pain using CRIES pain rating scale for both medical and surgical conditions, which contains (cry, spo2, heart rate, facial expression and sleep pattern). The study has been conducted for twelve weeks duration in the pediatric wards at medical and surgical hospitals in the Sulaimani city – Kurdistan region of Iraq between 1st March to 1st Jun 2019. Fifty early childhood aged between (1 month- 3years) were participated and assessed pre injectable medication procedure and after. CRIES pain scales were applied to the children and show that there are highly significant differences between pain and the physiological, behavior characteristics between pre and after the procedure in the p-value < .00001 such as crying was developed from high pitch crying to inconsolable in post-procedure. Consumption of O2 also increased. In terms of heart rate was increased up to 20% than baseline, while, in the post-procedure, the change was more than 20% of the baseline. Facial expression was also changed to contracted face in the post procedure. Sleeping from short interval to absent sleeping was shown. Significant variation between pre and post-procedure were assessed. Further variation between medical and surgical condition for mean score of every scale of CRIES were assessed. The implications of this study will impact on health professional’s education; practice and future research are also recommending.

Infant Cry Recognition System

Cries of infants can be seen as an indicator of pain. It has been proven that crying caused by pain, hunger, fear, stress, etc., show different cry patterns. The work presented here introduces a comparative study between the performance of two different classification techniques implemented in an automatic classification system for identifying two types of infants' cries, pain, and non-pain. The techniques are namely, Continuous Hidden Markov Models (CHMM) and Artificial Neural Networks (ANN). Two different sets of acoustic features were extracted from the cry samples, those are MFCC and LPCC, the feature vectors generated by each were eventually fed into the classification module for the purpose of training and testing. The results of this work showed that the system based on CDHMM have better performance than that based on ANN. CDHMM gives the best identification rate at 96.1%, which is much higher than 79% of ANN whereby in general the system based on MFCC features performed better than the one that utilizes LPCC features.

An Automatic Approach to Extract Features from the Infant’s Cry Signals

Responding to a new-born baby who communicates only through his/her cry is the most challenging issue in baby health care environment. Our Research work proposes an automatic algorithm to extract better features which can be further used to estimate accurately why a baby is crying by the analysis of its cry pattern. The signal processing techniques is applied to inspect the sound of these cries, by which it is possible to find the particular feature that carry the details about the circumstances that stimulated the cry and the coefficients is computed over LABVIEW. Features such as fundamental frequency (f0), spectral feature - Mel frequency cepstral coefficients (MFCCS) and Entropy based feature - Multi band spectral entropy signature (MBSES) were extracted. The extracted cry features are constructive and sensible, which will steer to acceptable classification and detection performance. Decoding baby cry with an Automatic cry detection (ACD) device is essential which will support the mother's to know and respond to their baby's needs, and in particular for the physician to treat the diseased infant in the early stage. This application can be used in the Obstetrics and Gynecology Clinique.

Characteristics and outcome of newborn admitted with acute bilirubin encephalopathy to a tertiary neonatal intensive care unit.

Acute bilirubin encephalopathy (ABE) still represents a significant cause of morbidity and mortality throughout the world, especially in developing countries. We aimed to determine the prevalence of ABE based on the Johnson bilirubin-induced neurologic dysfunction (BIND) score and to describe the discharge outcomes. We prospectively studied all newborns ≥ 35weeks with ABE by evaluating signs of mental sensorium, muscle tone, and cry patterns over 1year. 12%(81 out of 674) of the newborns admitted for neonatal hyperbilirubinemia had a BIND score > 1. Their admission age was 6 ± 4.1days; total serum bilirubin (TSB) was 31.2 ± 10mg/dL (range 17.5-75.2). Of these newborns, 40.7% and 21% had evidence of haemolysis and sepsis, respectively. Overall mortality was 9.9%; 58% of the newborns showed signs of mild-to-moderate BIND at discharge, while 32.1% survived with an apparently normal outcome. Admission BIND score was significantly correlated with admission TSB (r = 0.476, P < 0.001). Similarly, BIND score at discharge was correlated with admission TSB (r = 0.442, P < 0.001) and admission BIND score (r = 0.888, P < 0.001). The regression model showed that admission TSB (P < 0.001) and maternal illiteracy (P = 0.034) were predictors of the BIND score at admission, while admission BIND score was the best indicator of the discharge score (P < 0.001). ABE is still a major problem in our community. Admission TSB and maternal illiteracy are good predictors of bilirubin encephalopathy at admission and discharge.

Performance of Principal Component Analysis and Orthogonal Least Square on Optimized Feature Set in Classifying Asphyxiated Infant Cry Using Support Vector Machine

&lt;p&gt;An investigation into optimized support vector machine (SVM) integrated with principal component analysis (PCA) and orthogonal least square (OLS) in classifying asphyxiated infant cry was performed in this study. Three approaches were used in the classification; SVM, PCA-SVM, and OLS-SVM. Various numbers of features extracted from Mel-frequency Cepstral coefficient (MFCC) were tested to obtain the optimal parameters of SVM kernels. Once the optimal feature set is obtained, PCA and OLS selected the most significant features and the optimized SVM then classified the selected cry patterns. In PCA-SVM, eigenvalue-one-criterion (EOC), cumulative percentage variance (CPV) and the Scree test (SCREE) were used to select the most significant features. SVM with radial basis function (RBF) kernel was chosen in the classification stage. The classification accuracy and computation time were computed to evaluate the performance of each method. The best method for classifying asphyxiated infant cry is PCA-SVM with EOC since it produces the highest classification accuracy which is 94.84%. Using PCA-SVM, the classification process was performed in 1.98s only. The results also show that employing feature selection techniques could enhance the classifier performance.&lt;/p&gt;

Editor's Note MS#20162317 El Houchi et al - Neonatal jaundice: more than a number

Severe neonatal jaundice (unconjugated hyperbilirubinemia) may cause permanent brain injury and hearing loss in infants worldwide, including those born in developed countries. Bilirubin neurotoxicity is due to the effects of unbound unconjugated bilirubin in the central nervous system. The risk of kernicterus depends not only on the total serum bilirubin, but also factors such as the bilirubin-albumin binding capacity, prematurity, and other neonatal illnesses. In this volume of The Journal, El Houchi et al describe their use of the Bilirubin Induced Neurologic Dysfunction (BIND) Score to evaluate neurotoxicity in infants with severe hyperbilirubinemia, with the hope of improving our ability to detect infants who require timely exchange transfusions. The BIND score evaluates three aspects of the physical examination including mental status,muscle tone and cry pattern on a 0- to 3-point rating scale. In 220 near-term and full-terminfants admitted to their hospital with severe hyperbilirubinemia, El Houchi et al noted that regardless of the total serum bilirubin, infants with BIND scores of 3-4 or more were at increased risk for persistent neurologic abnormalities at 3-5 months of age. The etiology of jaundice for the infants in this study was not described, and the gestational age of the infants was not precisely known. These two factors suggest that further replication of these findings is needed to understand the usefulness of the BIND score across a variety of at-risk populations. However, in this study, El Houchi et al have shown that serial neurologic examinations are an important and cost-effective adjunct to the total serum bilirubin in the evaluation and management of jaundice that should be useful to pediatricians worldwide. Article page 51 ▶ Prediction of 3- to 5-Month Outcomes from Signs of Acute Bilirubin Toxicity in Newborn InfantsThe Journal of PediatricsVol. 183PreviewTo evaluate the ability of the bilirubin-induced neurologic dysfunction (BIND) score to predict residual neurologic and auditory disability and to document the relationship of BIND score to total serum bilirubin (TSB) concentration. Full-Text PDF

Prediction of 3- to 5-Month Outcomes from Signs of Acute Bilirubin Toxicity in Newborn Infants

To evaluate the ability of the bilirubin-induced neurologic dysfunction (BIND) score to predict residual neurologic and auditory disability and to document the relationship of BIND score to total serum bilirubin (TSB) concentration. The BIND score (assessing mental status, muscle tone, and cry patterns) was obtained serially at 6- to 8-hour intervals in 220 near-term and full-term infants with severe hyperbilirubinemia. Neurologic and/or auditory outcomes at 3-5 months of age were correlated with the highest calculated BIND score. The BIND score was also correlated with TSB. Follow-up neurologic and auditory examinations were performed for 145/202 (72%) surviving infants. All infants with severe acute bilirubin encephalopathy (BIND scores 7-9) either died or suffered residual neurologic and auditory impairment. Of 24 cases with moderate encephalopathy (BIND 4-6), 15 (62.5%) resolved following aggressive intervention and were normal at follow-up. Three of 73 infants with mild encephalopathy (BIND scores 1-3) but severe jaundice (TSB ranging 33.5-38 mg/dL; 573-650 µmol/L) had residual neurologic and/or auditory impairment. A BIND score ≥4 had a specificity of 87.3% and a sensitivity of 97.4% for predicting poor neurologic outcomes (receiver operating characteristic analysis). BIND scores trended higher with severe hyperbilirubinemia (r2 = 0.54, P < .005), but 5/39 (13%) infants with TSB ≥36.5 mg/dL (624 µmol/L) had BIND scores ≤3, and normal outcomes at 3-5 months. The BIND score can be used to evaluate the severity of acute bilirubin encephalopathy and predict residual neurologic and hearing dysfunction.

Baby Cry Detection in Domestic Environment Using Deep Learning

Automatic detection of a baby cry in audio signals is an essential step in applications such as remote baby monitoring. It is also important for researchers, who study the relation between baby cry patterns and various health or developmental parameters. In this paper, we propose two machine-learning algorithms for automatic detection of baby cry in audio recordings. The first algorithm is a low-complexity logistic regression classifier, used as a reference. To train this classifier, we extract features such as Mel-frequency cepstrum coefficients, pitch and formants from the recordings. The second algorithm uses a dedicated convolutional neural network (CNN), operating on log Mel-filter bank representation of the recordings. Performance evaluation of the algorithms is carried out using an annotated database containing recordings of babies (0-6 months old) in domestic environments. In addition to baby cry, these recordings contain various types of domestic sounds, such as parents talking and door opening. The CNN classifier is shown to yield considerably better results compared to the logistic regression classifier, demonstrating the power of deep learning when applied to audio processing.

Cry-based infant pathology classification using GMMs

Traditional studies of infant cry signals focus more on non-pathology-based classification of infants. In this paper, we introduce a noninvasive health care system that performs acoustic analysis of unclean noisy infant cry signals to extract and measure certain cry characteristics quantitatively and classify healthy and sick newborn infants according to only their cries. In the conduct of this newborn cry-based diagnostic system, the dynamic MFCC features along with static Mel-Frequency Cepstral Coefficients (MFCCs) are selected and extracted for both expiratory and inspiratory cry vocalizations to produce a discriminative and informative feature vector. Next, we create a unique cry pattern for each cry vocalization type and pathological condition by introducing a novel idea using the Boosting Mixture Learning (BML) method to derive either healthy or pathology subclass models separately from the Gaussian Mixture Model-Universal Background Model (GMM-UBM). Our newborn cry-based diagnostic system (NCDS) has a hierarchical scheme that is a treelike combination of individual classifiers. Moreover, a score-level fusion of the proposed expiratory and inspiratory cry-based subsystems is performed to make a more reliable decision. The experimental results indicate that the adapted BML method has lower error rates than the Bayesian approach or the maximum a posteriori probability (MAP) adaptation approach when considered as a reference method.

Teaching Parents About Normal Crying Patterns Reduces ED Visits

Most cases of frequent and prolonged crying in infants, a common chief complaint in pediatric emergency departments (EDs), are not due to an organic cause. In 2008–2009, all maternity hospitals and public health clinics in British Columbia implemented a public health program that educates parents about crying in normal infants and the dangers of shaking. The program involves a …

Classifying infant cry patterns by the Genetic Selection of a Fuzzy Model

Infant crying analysis is an important tool for identifying different pathologies at a very early stage of the life of a baby. Being able to perform this task with high accuracy is therefore important and required as a medical support system to assess a baby's health. In this research we propose an automatic classification model for infant crying for early disease detection. Our model mainly consists of two phases: (a) an acoustic features acquisition from the Mel Frequency Cepstral Coefficient and the Linear Predictive Coding from signal processing and (b) the selection/creation of an optimized fuzzy model through the Genetic Selection of a Fuzzy Model (GSFM) algorithm. GSFM searches for the best model by choosing a combination of a feature selection method, a type of fuzzy processing, a learning algorithm together with its associated parameters that best fit the input data. Our approach improves the predictive accuracy on the identification of the cause of crying and clearly helps to differentiate between normal and pathological cry. Experimental results show a significant accuracy improvement when using our optimized genetic selection method for most of the cases.

Characterization of eight Bacillus thuringiensis isolates originated from fecal samples of Fuzhou Zoo and Fuzhou Panda Center

In eight fecal samples of 5 herbivorous animals from Fuzhou Zoo and Fuzhou Panda Center were found eight Bacillus thuringiensis isolates. Obtained isolates were characterized by crystal microscopy, cry identification, and assay against the development of Eimeria tenella oocyst in chicken embryo. Bt WCB1, WCB2, WCB3 and WCB8, originated from horse, spotted deer, giant panda and lesser panda, respectively, all exhibited bipyramidal and cuboidal crystal and harbored the same cry genes, which were cry1Cb, cry1Db, cry1Fa, cry1Ib and cry2Ab. WCB7, a Bt isolate with bipyramidal crystal from zebra, showed a different cry pattern, cry1Cb, cry1Db, cry1Fa and cry1Ia. Bt WCB6, the third Bt isolate from giant panda, also contained bipyramidal crystal, however, harbored cry1Ib only. It was noted that Bt isolate WCB5 contained cuboidal crystal and harbored an unknown cry3 gene. It was very interesting that no cry genes were detected from Bt isolate WCB4 with dot-like crystal. Parasporal crystal proteins of WCB3, WCB4 and WCB7 obviously inhibited the development of E. tenella oocyst in chicken embryo.

Preventing Early Infant Sleep and Crying Problems and Postnatal Depression: A Randomized Trial

To evaluate a prevention program for infant sleep and cry problems and postnatal depression. Randomized controlled trial with 781 infants born at 32 weeks or later in 42 well-child centers, Melbourne, Australia. Follow-up occurred at infant age 4 and 6 months. The intervention including supplying information about normal infant sleep and cry patterns, settling techniques, medical causes of crying and parent self-care, delivered via booklet and DVD (at infant age 4 weeks), telephone consultation (8 weeks), and parent group (13 weeks) versus well-child care. Outcomes included caregiver-reported infant night sleep problem (primary outcome), infant daytime sleep, cry and feeding problems, crying and sleep duration, caregiver depression symptoms, attendance at night wakings, and formula changes. Infant outcomes were similar between groups. Relative to control caregivers, intervention caregivers at 6 months were less likely to score >9 on the Edinburgh Postnatal Depression Scale (7.9%, vs 12.9%, adjusted odds ratio [OR] 0.57, 95% confidence interval [CI] 0.34 to 0.94), spend >20 minutes attending infant wakings (41% vs 51%, adjusted OR 0.66, 95% CI 0.46 to 0.95), or change formula (13% vs 23%, P < .05). Infant frequent feeders (>11 feeds/24 hours) in the intervention group were less likely to have daytime sleep (OR 0.13, 95% CI 0.03 to 0.54) or cry problems (OR 0.27, 95% CI 0.08 to 0.86) at 4 months. An education program reduces postnatal depression symptoms, as well as sleep and cry problems in infants who are frequent feeders. The program may be best targeted to frequent feeders.

Preliminary evaluation of a primary care intervention for cry-fuss behaviours in the first 3-4 months of life (‘The Possums Approach’): effects on cry-fuss behaviours and maternal mood

Problem crying in the first few months of life is both common and complex, arising out of multiple interacting and co-evolving factors. Parents whose babies cry and fuss a lot receive conflicting advice as they seek help from multiple health providers and emergency departments, and may be admitted into tertiary residential services. Conflicting advice is costly, and arises out of discipline-specific interpretations of evidence. An integrated, interdisciplinary primary care intervention ('The Possums Approach') for cry-fuss problems in the first months of life was developed from available peer-reviewed evidence. This study reports on preliminary evaluation of delivery of the intervention. A total of 20 mothers who had crying babies under 16 weeks of age (average age 6.15 weeks) completed questionnaires, including the Crying Patterns Questionnaire and the Edinburgh Postnatal Depression Scale, before and 3-4 weeks after their first consultation with trained primary care practitioners. Preliminary evaluation is promising. The Crying Patterns Questionnaire showed a significant decrease in crying and fussing duration, by 1h in the evening (P=0.001) and 30 min at night (P=0.009). The median total amount of crying and fussing in a 24-h period was reduced from 6.12 to 3h. The Edinburgh Postnatal Depression Scale showed a significant improvement in depressive symptoms, with the median score decreasing from 11 to 6 (P=0.005). These findings are corroborated by an analysis of results for the subset of 16 participants whose babies were under 12 weeks of age (average age 4.71 weeks). These preliminary results demonstrate significantly decreased infant crying in the evening and during the night and improved maternal mood, validating an innovative interdisciplinary clinical intervention for cry-fuss problems in the first few months of life. This intervention, delivered by trained health professionals, has the potential to mitigate the costly problem of health professionals giving discipline-specific and conflicting advice post-birth.

Infant difficulty and early weight gain: does fussing promote overfeeding?

Authors have recently suggested that difficult temperament in infancy may be associated with rapid weight gain, but no previous studies actually report associations between temperament and feeding as a response to infant distress. The purpose of the present study was to examine whether greater infant difficulty elicits more feeding, which in turn leads to more rapid weight gain in early infancy. One hundred fifty-four mother-infant pairs were visited at 3 and 6 months in their homes. Besides anthropometric measures, mothers kept a 24-h diary of their infants' sleep, cry and feed patterns, and answered questions regarding feeding and infant difficultness. The results showed that feeding occurred as a response to nearly half (48%) of the crying intervals recorded, though it more often occurred in the absence of crying (83%). Mothers were most likely to report holding or rocking their infant as the first strategy they would employ if their baby fussed or cried. A regression analysis that included crying, feeding, weaning, sleep and infant weight revealed maternal reports of numbers of feeds per day as the only variable that predicted weight gain from 3 to 6 months. Infant crying is often followed by feeding, and more frequent feeding may promote more rapid weight gain. However, feeding frequency in the first few months appears to be more a matter of maternal discretion than a yoked response to temperamental difficulty. This does not preclude the possibility that overfeeding in later infancy could be tied to temperamental difficulty and subsequently related to overweight in early childhood.